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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Das, Ranajit Upadhyai, Priyanka |
| Abstract | Background The utilization of biological data to infer the geographic origins of human populations has been a long standing quest for biologists and anthropologists. Several biogeographical analysis tools have been developed to infer the geographical origins of human populations utilizing genetic data. However due to the inherent complexity of genetic information these approaches are prone to misinterpretations. The Geographic Population Structure (GPS) algorithm is an admixture based tool for biogeographical analyses and has been employed for the geo-localization of various populations worldwide. Here we sought to dissect its sensitivity and accuracy for localizing highly admixed groups. Given the complex history of population dispersal and gene flow in the Indian subcontinent, we have employed the GPS tool to localize five South Asian populations, Punjabi, Gujarati, Tamil, Telugu and Bengali from the 1000 Genomes project, some of whom were recent migrants to USA and UK, using populations from the Indian subcontinent available in Human Genome Diversity Panel (HGDP) and those previously described as reference. Results Our findings demonstrate reasonably high accuracy with regards to GPS assignment even for recent migrant populations sampled elsewhere, namely the Tamil, Telugu and Gujarati individuals, where 96%, 87% and 79% of the individuals, respectively, were positioned within 600 km of their native locations. While the absence of appropriate reference populations resulted in moderate-to-low levels of precision in positioning of Punjabi and Bengali genomes. Conclusions Our findings reflect that the GPS approach is useful but likely overtly dependent on the relative proportions of admixture in the reference populations for determination of the biogeographical origins of test individuals. We conclude that further modifications are desired to make this approach more suitable for highly admixed individuals. |
| Related Links | https://bmcgenomdata.biomedcentral.com/counter/pdf/10.1186/s12863-017-0579-2.pdf |
| Ending Page | 31 |
| Page Count | 11 |
| Starting Page | 21 |
| File Format | HTM / HTML |
| ISSN | 27306844 |
| DOI | 10.1186/s12863-017-0579-2 |
| Journal | BMC Genomic Data |
| Issue Number | 1 |
| Volume Number | 18 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2017-12-28 |
| Access Restriction | Open |
| Subject Keyword | Life Sciences Animal Genetics and Genomics Microbial Genetics and Genomics Plant Genetics and Genomics Genetics and Population Dynamics Geographical population structure (GPS) Admixture Highly admixed populations Geo-localization South Asian population history |
| Content Type | Text |
| Resource Type | Article |
| Subject | Health Informatics Genetics |
| Journal Impact Factor | 1.9/2023 |
| 5-Year Journal Impact Factor | 1.9/2023 |
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